code: def test_number_of_missing_values(sparse_data):
      X, y, categorical = sparse_data
      mf = meta_features.metafeatures["NumberOfMissingValues"](
          X, y, logging.getLogger("Meta"), categorical
      )
      assert 0 == mf.value
  
imports: import logging
  import os
  import arff
  import numpy
  from scipy import sparse
  from sklearn.impute import SimpleImputer
  from sklearn.preprocessing import StandardScaler
  import autosklearn.metalearning.metafeatures.metafeatures
  from autosklearn.pipeline.components.data_preprocessing.feature_type import FeatTypeSplit
  import pytest
label_desc: Use image node_id 4 for calling a global function with example usage: test_number_of_missing_values(sparse_data) without return types